D Question 7 4 pts For a log regression model that had multiple predictors has a summary that is partially provided below: Deviance Residuals: Min 1Q Median -1.251 - 1.164 1.128 30 1.148 Max 1.218 Coefficients: Estimate Std. Error z value Pr(>21) (Intercept) 1.372e-91 8.129e-e2 1.688 @.e914. gendermale -1.345e-82 3.6e9e-e2 -0.373 0.7093 gendernon-binary 5.966e-82 3.1e3e-eie. 192 0.8475 purchaseyes -1.438e-1 3.6e3e-e2 -3.991 6.57e-e5 *** - pets 6.297e-84 7.739e-e3 0.081 0.9351 salary -6.781e-07 1.199e-86 - -0.566 0.5716 Signif. codes: ***** 8.681 **** 2.81 *** 0.95 0.1'' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 17113 on 12344 degrees of freedom Residual deviance: 17096 on 12339 degrees of freedom AIL: 1718 Number of Fisher Scoring iterations: 3 If we are using backwards elimination to determine the best predicting model, which variable would we remove for the next model? Question 8 9 pts Write two lines of code in R that creates a log regression model that predicts exposure to the ad in network 1 with gender and salary and then summarizes the model. Call the model model.net Remember the data frame referenced is exan.data. Edit View Insert Format Tools Table 12pt Paragraph v BI U A 207 * E * The scenario for the data in exam3.data is that you are a company interested in understanding your customer base. Each of the 12345 rows is a different person. Here is the breakdown of columns: id : just an identifier for each observation gender: the gender of the individual (male, female, and non-binary) hand: the dominant hand of the individual (R for right-handed, L for left-handed) pets: the amount of pets the individual has salary: the estimated salary of the individual net1: exposure to an ad in Network 1 (1 if exposed to the ad in this network, O if not exposed to the ad in this network). net2: exposure to an ad in Network 2 (1 if exposed to the ad in this network, O if not exposed to the ad in this network). purchase: if the individual made a purchase (yes if they made a purchase, no if they didn't make a purchase)